TY - JOUR
T1 - Regulatory assessment of drug dissolution profiles comparability via maximum deviation
AU - Moellenhoff, Kathrin
AU - Dette, Holger
AU - Kotzagiorgis, Evangelos
AU - Volgushev, Stanislas
AU - Collignon, Olivier
N1 - Funding Information:
This work has been supported in part by the Collaborative Research Center “Statistical modeling of nonlinear dynamic processes” (SFB 823, Project C1,T1) of the German Research Foundation (DFG). Kathrin Möllenhoff's research has received funding from the European Union Seventh Framework Programme [FP7 20072013] under grant agreement No. 602552 (IDEAL ‐ Integrated Design and Analysis of small population group trials). The Authors would like to express their gratitude to Radu Popescu, Alessandro Spina, and Alexandar Rusanov from EMA for legal advice and for facilitating access to EMA datasets, Ina‐Christine Rondak and Kevin Blake (EMA) for their useful internal review of the manuscript, and to Professor Stephen Senn from the Luxembourg Institute of Health for suggesting this collaboration.
Publisher Copyright:
Copyright © 2018 John Wiley & Sons, Ltd.
PY - 2018/9/10
Y1 - 2018/9/10
N2 - In drug development, comparability of dissolution profiles of 2 different formulations is usually assessed using the similarity factor f2. In practice, the drug dissolution profiles are deemed similar if the f2 exceeds 50, which occurs when a 10% maximum difference in the mean percentage of the dissolved drug at each time point between test and reference formulation is obtained. According to the Guideline on the Investigation of Bioequivalence (CPMP/EWP/QWP/1401/98 Rev. 1/ Corr **) use of the f2 is however restricted by a set of validity conditions. If some of these conditions are not satisfied, the f2 is not considered suitable, and alternative statistical methods are needed. In this article, we propose an inferential framework based on the maximum deviation between curves to test the comparability of drug dissolution profiles. The new methodology is applicable regardless whether the validity criteria of the f2 are met or not. Contrary to the f2, this approach also integrates the variability of the measurements over time and not only their average. To benchmark our method, we performed simulations informed by 3 real case studies provided by the European Medicines Agency and extracted from dossiers submitted to the Centralised Procedure for Marketing Authorisation Application. In the scenarios of the simulation study, the new method controlled its type I error rate when the maximum deviation was greater than the similarity acceptance limit of 10%. The power exceeded 80% for small values of the maximum deviation, while the test was more conservative for intermediate ones. Our results were also very robust to sampling variations. Based on these positive findings, we encourage applicants to consider the new maximum deviation–based method as a valid alternative to the f2, especially when the validity criteria of the latter are not met.
AB - In drug development, comparability of dissolution profiles of 2 different formulations is usually assessed using the similarity factor f2. In practice, the drug dissolution profiles are deemed similar if the f2 exceeds 50, which occurs when a 10% maximum difference in the mean percentage of the dissolved drug at each time point between test and reference formulation is obtained. According to the Guideline on the Investigation of Bioequivalence (CPMP/EWP/QWP/1401/98 Rev. 1/ Corr **) use of the f2 is however restricted by a set of validity conditions. If some of these conditions are not satisfied, the f2 is not considered suitable, and alternative statistical methods are needed. In this article, we propose an inferential framework based on the maximum deviation between curves to test the comparability of drug dissolution profiles. The new methodology is applicable regardless whether the validity criteria of the f2 are met or not. Contrary to the f2, this approach also integrates the variability of the measurements over time and not only their average. To benchmark our method, we performed simulations informed by 3 real case studies provided by the European Medicines Agency and extracted from dossiers submitted to the Centralised Procedure for Marketing Authorisation Application. In the scenarios of the simulation study, the new method controlled its type I error rate when the maximum deviation was greater than the similarity acceptance limit of 10%. The power exceeded 80% for small values of the maximum deviation, while the test was more conservative for intermediate ones. Our results were also very robust to sampling variations. Based on these positive findings, we encourage applicants to consider the new maximum deviation–based method as a valid alternative to the f2, especially when the validity criteria of the latter are not met.
KW - bioequivalence
KW - comparison of dissolution profiles
KW - equivalence testing
KW - maximum deviation
UR - http://www.scopus.com/inward/record.url?scp=85051202208&partnerID=8YFLogxK
U2 - 10.1002/sim.7689
DO - 10.1002/sim.7689
M3 - Article
C2 - 29862526
AN - SCOPUS:85051202208
SN - 0277-6715
VL - 37
SP - 2968
EP - 2981
JO - Statistics in Medicine
JF - Statistics in Medicine
IS - 20
ER -